Recent advances in the field of nonlinear dynamics and "chaos" theory have provided new conceptual models as well as novel data analytical techniques applicable to the study of biological systems. These powerful models and analytical techniques are now available for use in studies aimed at evaluating the effects of alcohol on a host of biological systems, and may provide a new view of how alcohol affects brain function. In addition, specific new quantitative techniques that estimate nonlinear properties of systems may provide the means for identifying new biological measures of risk for the development of alcohol abuse and dependence. The series of investigations to be described have the overall goal of developing a theoretical framework based on nonlinear dynamics by which the actions of alcohol on the EEG can be studied. New EEG measurement techniques will be further developed which will assess data collected from human subjects prior to and following challenge with acute doses of ethanol and placebo. The populations to be studied include Caucasian and Native American subjects with alcoholic fathers who are at high risk for the development of alcoholism and their matched controls. We will also evaluate EEG data collected from Asian American subjects with ALDH2*2 alleles who are at very low risk for the development of alcohol dependence and abuse and their matched controls. In collaboration with our colleagues at Los Alamos National Laboratories, we will also attempt to develop predictive models using nonlinear techniques. While the studies described in this proposal will be utilizing EEG data as the primary variable, the development of these new techniques will also hasten the use of this technology in other biological systems relevant to the study of alcohol such as biochemical and behavioral assay variables.